by PhilipJ on 28 May 2008

I can’t recall offhand, but it was probably in Genius where Gleick, or maybe some famous figure in the history of science, joked about the way Richard Feynman solved problems. It went something like this:

Write down the problem.

Think very hard.

Write down the solution.

While this is obviously wouldn’t have worked for his brief stint as a biologist, for someone of Feynman’s intellect you might sometimes imagine it to be close to the truth for solving physics problems. In fact, Feynman solved problems the same way we all try to solve problems. From a wonderful essay titled Richard Feynman and The Connection Machine, W. Daniel Hillis recounts Feynman’s internship at a startup computer company:

For Richard, figuring out these problems was a kind of a game. He always started by asking very basic questions like, “What is the simplest example?” or “How can you tell if the answer is right?” He asked questions until he reduced the problem to some essential puzzle that he thought he would be able to solve. Then he would set to work, scribbling on a pad of paper and staring at the results. While he was in the middle of this kind of puzzle solving he was impossible to interrupt. “Don’t bug me. I’m busy,” he would say without even looking up. Eventually he would either decide the problem was too hard (in which case he lost interest), or he would find a solution (in which case he spent the next day or two explaining it to anyone who listened). In this way he worked on problems in database searches, geophysical modeling, protein folding, analyzing images, and reading insurance forms.

This idea of solving little puzzles as the way we do science is something André and I often talked about as undergrads, and it still rings true for me. Turning a large problem into a host of smaller ones makes research seem far more tractable and gives real, shorter-term goals to keep me motivated.

The article also makes mention of “crazy” ideas, and how Feynman was excited by them:

His reaction was unequivocal, “That is positively the dopiest idea I ever heard.” For Richard a crazy idea was an opportunity to either prove it wrong or prove it right. Either way, he was interested.

I think the combination of those two quotes forms a good philosophy for doing science. Crazy ideas are often interesting ideas (if they’re right it could be very exciting!), and after working on a problem and deciding it is too hard, you can’t be afraid to lose interest and try something else.

Two minutes into the video it’s actually Hans Bethe. Feynman was surely exceptionally brilliant but I don’t think that’s the point Philip is trying to make. You can hardly argue against the idea that Feynman solved large problems by breaking them up into smaller ones that were more manageable. He might have done it more creatively and quickly than anyone else, but let’s drop some of the hyperbole.

Idolizing scientists can be fun but it’s a terrible approach to discussing the history or practice of science. It diminishes the hard work of the people that are idolized and more importantly diminishes the work of those that laid the foundations for their success and the contemporaries that were invariably on the verge of making similar contributions. Let’s not forget that Feynman shared his Nobel prize with Schwinger and Tomonaga (even if Feynman’s approach has had wider ranging or more enduring consequences—I’ve heard this but I’m not qualified to comment). We don’t need hyperbole to respect people that made amazing contributions to science. Everyone makes mistakes and everyone struggles with hard problems.

I almost didn’t study physics because I thought it was pointless to try since I could see I wasn’t a “magician.” In the end I looked around at the other people that were somehow managing to do it and I thought I’d give it a try. I’m very glad that I did.

What I meant was that Feynman is a personification of science. He represents a vast number of ideas for how to do great science, the perils and ethics of science, how to look to the future (he talked about nanotech, miniaturization of computers, computer vision, quantum computing, etc long before they came of age), how to reduce problems, how to question, how to challenge authority, how to be inspired by teaching, and unlearn things in old age so as to continue to make contributions. He was connected with programming and hacker culture via Thinking Machines, and biology. And how to popularize science.

By studying the “history of science” at a surface level, I feel that people tend to miss out on the essential cognitive aspects of science. They tend to conclude that science is a job.

I think if you read some other posts on the blog you’ll see that neither Phil nor I see science as just a job. It’s an extraordinary thing to be a part of and it has elements of hobby, lifelong passion, and yes, job. It’s great that Feynman took such pleasure in finding things out and I hope he inspired a lot of people to do the same. I just want people to remember that pursuing science, even as a career, doesn’t require you to be some kind of super genius.

The bigger risk of studying the history of science at a surface level is concluding that it’s for the lone genius labouring in isolation. Science is broader than that caricature.

Part of the problem with science is misunderstanding that ideas are typically developed in parallel by many people. Cognitive limitations seems to limit “who gets the credit,” and a result of network effects and cognitive limitations, only one person (often the person who developed a theory later than the others but marketed it better) gets the credit for “the” theory.

I’m not sure that people “are” geniuses. I think people become geniuses by training. People like Feynman and Einstein just trained themselves to be geniuses.

And because geniuses train themselves, they tend to exhibit a certain algorithm. Which we can learn from, to do better science, become smarter, or contribute more to humanity. The biographies of great scientists help us learn about positive (and negative) traits of behavior.

I disagree with your statement. Some people “are” geniuses. How else can you explain a child prodigy like Mozart, composing music and playing with trained adults when he was less than 10 years old? The linguistic and mathematical abilities displayed by Gauss (and many other mathematicians) at an early age?

I think Feynman, Einstein, and many other scientists, artists, writers, musicians, etc. have an innate talent that they continue to develop throughout their life. There is no doubt that these people work hard, but to deny that they have an innate gift seems absurd.

Yes, but look at the thousands of hours of practice that Mozart was put through as a child. He succeeded in a way others hadn’t, but he didn’t magically manifest all of those skills.

I can’t speak to Gauss, and I’m sure there are the few rare talents who just have different brains (Einstein perhaps), but I think its more promising to realize that most genius is just efficiently applied practice, by folks who were incredibly obsessive (and maybe a little crazy).

Well, from the perspective of neuroscience and evolution, it seems reasonable that a person could be born with one or several faculties of the brain more well-developed. But people are only evolved to think about things like the social, kinesthetic, finding food, puzzle solving, leadership, using tools, mating, and raising children, with various regions of the brain lighting up in combination for these tasks. So it seems to me that the combination of these different components of intelligence, statistically, will innately make people’s brains fall into a bubble where people are “pretty good apes” — at solving the small number (200?) of different types of problems that humans evolved to solve.

This means if you want to teach a human abstract mathematics, they’re not naturally good at it, since we’re not evolved to do that. If we were evolved to do abstract mathematics, the average guy on the street would be way freaking better at it than Gauss. Us humans can take our existing mental faculties and train them to solve new types of problems, like say number theory. This works best when the brain is still developing and trimming down all the connections it doesn’t need.

So I wouldn’t think “genius” could really be innate, since there isn’t enough flexibility in the “bubble of potential brains” to make people naturally be able to do something “genius” like symbolic math (even though doing “genius” level mathematics is probably easier in the absolute sense than throwing a football, we subjectively view Gauss as a genius and the average jock as not very smart, because making the human brain do symbolic math requires a lot of retraining). So I think genius is mostly the result of obsessively retraining the connections in the brain from a young age. And it also tends to make people crazy, and flake out in life (look at Grigori Perelman or the Unibomber), since the rest of their life skills are so underdeveloped.